… use of the Wave-U-Net architecture for speech enhancement… to the speech enhancement
task on the Voice Bank corpus (… is based on the repeated application of dilated convolutions …

… In this work we proposed U-net-based neural network architectures in which recurrent-convolutional
pairs are used at different levels. The obtained result show that the proposed …

… U-Net with a gated recurrent unit and an efficient channel attention mechanism for real-time
single-channel speech … Additionally, the U-Net architecture uses gated recurrent units (GRU), …

… variational U-Net architecture over its classic, non-variational version in signal enhancement
… with the variational U-Net compared to the recurrent mask estimation network baseline. …

… The U-Net structure is a well known architecture composed as a convolutional autoencoder
… Speech enhancement with lstm recurrent neural networks and its application to noise-robust …

… The recurrent U-net architecture was extended in [11], where recurrent layers were added
… In the present work, we propose a U-net-based neural network for speech enhancement. In …

… is the proposal of four simple enhancements to the Wave-U-Net architecture that contribute
to the … and recognition using multi-task learning of long short-term memory recurrent neural …

… -based methods, such as the deep recurrent neural network (DRNN), SE generative … based
on a multi-task learning U-Net (MTU-Net) architecture to provide a better estimate of the IRM …

… use the LRS2BBC dataset [25] to learn a model that can work robustly in real-world environments.
Moreover, we extend the Unet using the proposed Recurrent… our model architecture in …

… Recently speech enhancement auto-encoders with recurrent … In this work, several architectures
were tested, including: (1) a pipeline architecture of LSTM-based speech enhancement …